Image processing device, image projection apparatus, and image processing method

ABSTRACT

An image processing device includes a resolution reducer, a detector, and a corrector. The resolution reducer generates, from an input image, low resolution images for pixel shift display being lower in resolution than the input image. The detector detects portions of the low resolution images corresponding to a specific pattern in which image quality degradation may occur. The corrector performs specific correction processing to reduce the image quality degradation on the portions of the low resolution images corresponding to the specific pattern.

CROSS-REFERENCE TO RELATED APPLICATION

This patent application is based on and claims priority pursuant to 35U.S.C. § 119(a) to Japanese Patent Application No. 2017-011489, filed onJan. 25, 2017, in the Japan Patent Office, the entire disclosure ofwhich is hereby incorporated by reference herein.

BACKGROUND Technical Field

Aspects of the present disclosure relate to an image processing device,an image projection apparatus, and an image processing method.

Related Art

There have been conventionally known image projection apparatuses thatproject images onto a screen. Some image projection apparatuses candisplay two images generated from one image in such a manner that thetwo images are shifted from each other, that is, perform pixel shiftdisplay of the two images, to increase image display resolution.

SUMMARY

In an aspect of the present disclosure, there is provided an imageprocessing device that includes a resolution reducer, a detector, and acorrector. The resolution reducer generates, from an input image, lowresolution images for pixel shift display being lower in resolution thanthe input image. The detector detects portions of the low resolutionimages corresponding to a specific pattern in which image qualitydegradation may occur. The corrector performs specific correctionprocessing to reduce the image quality degradation on the portions ofthe low resolution images corresponding to the specific pattern.

In another aspect of the present disclosure, there is provided an imageprocessing method that includes generating, from an input image, lowresolution images for pixel shift display being lower in resolution thanthe input image; detecting portions of the low resolution imagescorresponding to a specific pattern in which image quality degradationmay occur; and performing specific correction processing to reduce theimage quality degradation on the portions of the low resolution imagescorresponding to the specific pattern.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

A more complete appreciation of the disclosure and many of the attendantadvantages and features thereof can be readily obtained and understoodfrom the following detailed description with reference to theaccompanying drawings, wherein:

FIG. 1 is a diagram illustrating a configuration of a projectoraccording to a first embodiment of the present disclosure;

FIG. 2 is a block diagram illustrating a functional configuration of animage controller according to the first embodiment of the presentdisclosure;

FIG. 3 is a flowchart of a procedure of processing by the imagecontroller according to the first embodiment of the present disclosure;

FIGS. 4A and 4B are diagrams illustrating examples of resolutionreduction processing by a resolution reducer according to the firstembodiment of the present disclosure;

FIGS. 5A to 5C are diagrams illustrating examples of specific patterndetection processing by a detector according to the first embodiment ofthe present disclosure;

FIGS. 6A to 6D are diagrams illustrating examples (first examples) ofdetection processing of candidate pixels for correction processing by afirst detector according to the first embodiment of the presentdisclosure;

FIGS. 7A and 7B are diagrams illustrating examples (first examples) ofdetection processing of pixels other than target pixels of thecorrection processing by a second detector according to the firstembodiment of the present disclosure;

FIG. 8 is a diagram illustrating an example (first examples) ofcorrection processing by a corrector according to the first embodimentof the present disclosure;

FIGS. 9A to 9D are diagrams illustrating examples (second examples) ofdetection processing of candidate pixels for the correction processingby the first detector according to the first embodiment of the presentdisclosure;

FIG. 10 is a diagram illustrating an example (second example) ofdetection processing of pixels other than target pixels of thecorrection processing by the second detector according to the firstembodiment of the present disclosure;

FIG. 11 is a diagram illustrating an example (second example) ofcorrection processing by the corrector according to the first embodimentof the present disclosure;

FIG. 12 is a diagram illustrating an example of a filter used in avariation of the correction processing by the corrector according to thefirst embodiment of the present disclosure;

FIG. 13 is a block diagram illustrating a functional configuration of animage controller according to a second embodiment of the presentdisclosure;

FIG. 14 is a flowchart of a procedure of processing by the imagecontroller according to the second embodiment of the present disclosure;

FIGS. 15A to 15D are diagrams illustrating examples of a smoothingfilter and a sharpening filter used by the image controller according tothe second embodiment of the present disclosure; and

FIG. 16 is a block diagram illustrating a functional configuration ofthe image controller according to a variation of the second embodimentof the present disclosure.

The accompanying drawings are intended to depict embodiments of thepresent invention and should not be interpreted to limit the scopethereof. The accompanying drawings are not to be considered as drawn toscale unless explicitly noted.

DETAILED DESCRIPTION

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the presentinvention. As used herein, the singular forms “a”, “an” and “the” areintended to include the plural forms as well, unless the context clearlyindicates otherwise.

In describing embodiments illustrated in the drawings, specificterminology is employed for the sake of clarity. However, the disclosureof this specification is not intended to be limited to the specificterminology so selected and it is to be understood that each specificelement includes all technical equivalents that have a similar function,operate in a similar manner, and achieve a similar result.

A first embodiment of the present disclosure will be described belowwith reference to the drawings.

Configuration of Projector 100

FIG. 1 is a diagram illustrating a configuration of a projector 100according to a first embodiment of the present disclosure. The projector100 is an example of an image projection apparatus according to thepresent disclosure. The projector 100 can generate a display targetimage based on image data input from the outside (for example, apersonal computer (PC)), and project the display target image onto ascreen 150 (an example of a projection plane according to the presentdisclosure).

As illustrated in FIG. 1, the projector 100 includes a power supply 101,a main switch 102, an operation unit 103, an external interface (I/F)104, a fan 105, a system control unit 110, and an optical engine 120.

The power supply 101 supplies power to individual components of theprojector 100 (for example, the system control unit 110, the fan 105,the optical engine 120, and others). The main switch 102 switches on andoff the power supply to the projector 100 by user operation.

The operation unit 103 accepts various user operations. For example, theoperation unit 103 is provided on the top of the projector 100 andincludes input buttons, a display, and others. The external I/F 104 iscoupled to an external device (for example, a PC, a digital camera, orthe like) to control input of image data from the external device. Thefan 105 cools a light source 121 of the optical engine 120.

The system control unit 110 has an image controller 111 and a drivecontroller 112. The image controller 111 is an example of an imageprocessing device according to the present embodiment. The imagecontroller 111 generates an image to be projected onto the screen 150 bythe optical engine 120, based on the image data input from the externalI/F 104. The drive controller 112 controls a movable unit 126 providedin an image generation unit 123 of the optical engine 120 to control theposition of a digital micromirror device (DMD) 127 provided in themovable unit 126.

The optical engine 120 is an example of a projector engine according tothe present embodiment. The optical engine 120 is controlled by thesystem control unit 110 to project the image generated by the imagecontroller 111 onto the screen 150. The optical engine 120 has a lightsource 121, an illumination optical unit 122, an image generation unit123, and a projection optical unit 124.

The light source 121 emits light. The light source 121 may be a mercuryhigh-pressure lamp, a xenon lamp, a light emitting diode (LED), or thelike, for example.

The illumination optical unit 122 guides the light emitted from thelight source 121 to the DMD 127. The illumination optical unit 122 has acolor wheel, a light tunnel, a relay lens, and the like, for example.

The image generation unit 123 has a stationary unit 125 and the movableunit 126. The movable unit 126 has the DMD 127. The movable unit 126 iscontrolled in the position with respect to the stationary unit 125 bythe drive controller 112 of the system control unit 110. The DMD 127 iscontrolled by the image controller 111 of the system control unit 110 tomodulate the light guided via the illumination optical unit 122 andgenerate a projection image.

The projection optical unit 124 enlarges the projection image generatedby the DMD 127 and projects the same onto the screen 150. The projectionoptical unit 124 has a plurality of projection lenses, a mirror, and thelike, for example.

The thus configured projector 100 can perform appropriate correctionprocessing on images under control of the image controller 111 at thetime of pixel shift display of the images, to increase display imagequality. This will be specifically described below.

Functional Configuration of Image Controller 111

FIG. 2 is a block diagram illustrating a functional configuration of theimage controller 111 according to the first embodiment of the presentdisclosure. In the example of FIG. 2, the image controller 111 includesan image obtainer 201, a resolution reducer 202, an image output unit203, a detector 211, and a corrector 212.

The image obtainer 201 obtains an image input from the outside. Forexample, the image obtainer 201 obtains an ultra high definition (UHD)input image of 3840×2160 pixels.

From the input image obtained by the image obtainer 201, the resolutionreducer 202 generates low resolution images for pixel shift displaylower in resolution than the input image. Specifically, the resolutionreducer 202 generates two low resolution images from the one input imageobtained by the image obtainer 201. For example, the resolution reducer202 generates full high definition (FHD) low resolution images of1920×1080 pixels from the UHD input image. An example of the resolutionreduction processing by the resolution reducer 202 will be describedlater with reference to FIGS. 4A and 4B.

The detector 211 detects a specific pattern from the input imageobtained by the image obtainer 201. The detector 211 specifies portionscorresponding to a specific pattern in the low resolution imagesgenerated by the resolution reducer 202. The specific pattern in theembodiment refers to a portion in which relatively strong image blurring(equivalent to image quality degradation in the present disclosure) canbe caused when two low resolution images are displayed with a pixelshift. The specific pattern may be formed from a single pixel or aplurality of pixels. In the embodiment, the detector 211 detects anoblique line and an isolated point as specific patterns. An example ofspecific pattern detection processing by the detector 211 will bedescribed later with reference to FIGS. 5A to 5C.

The detector 211 has a first detector 211A and a second detector 211B.The first detector 211A detects pixels with a density of 25% or more(that is, pixels with an average density of 25% of 2×2 pixels in thecorresponding input image) in the low resolution images as candidatepixels for the correction processing. The second detector 211B detectspixels not matching the specific pattern, out of the candidate pixelsfor the correction processing detected by the first detector 211A, (thatis, pixels not constituting an oblique line or an isolated point) aspixels other than target pixels of the correction processing). Anexample of the detection processing of the candidate pixels for thecorrection processing by the first detector 211A will be described laterwith reference to FIGS. 6A to 6D. An example of the detection processingof pixels other than target pixels of the correction processing by thesecond detector 211B will be described later with reference to FIGS. 7Aand 7B.

The corrector 212 performs the specific correction processing forreducing image blurring in portions corresponding to the specificpattern detected by the detector 211 in the low resolution imagesgenerated by the resolution reducer 202. Specifically, the portionscorresponding to the specific pattern refer to the candidate pixels forthe correction processing detected by the first detector 211A, which arenot detected as pixels other than target pixels of the correctionprocessing by the second detector 211B. In the embodiment, the corrector212 performs emphasis processing as “specific correction processing”. Anexample of the correction processing by the corrector 212 will bedescribed later with reference to FIG. 8.

The image output unit 203 outputs the low resolution images generated bythe resolution reducer 202 (the low resolution images having undergonethe correction processing by the corrector 212) to the image generationunit 123 (see FIG. 1). Accordingly, the image output unit 203 causes theoptical engine 120 to perform pixel shift display of the low resolutionimages onto the screen 150. The optical engine 120 alternately switchesbetween the two low resolution images at a frame rate (for example, 120fps) higher than a normal frame rate (for example, 60 fps) to performthe pixel shift display of the two low resolution images. The pixelshift display is implemented by the DMD 127 shifting in synchronizationwith the switching timing between the two low resolution images underthe control of the drive controller 112.

The image controller 111 includes components, for example, such ascentral processing unit (CPU), a read only memory (ROM), and a randomaccess memory (RAM). The functions of the image controller 111 describedabove are implemented by the CPU executing a program recorded on the ROMor the like, for example. This program may be installed in advance intothe image controller 111 and provided together with the image controller111 or may be provided from the outside separately from the imagecontroller 111 and installed into the image controller 111. In thelatter case, the program may be provided by an external storage medium(for example, a USB memory, a memory card, a CD-ROM, or the like) or maybe provided by downloading from a server on a network (for example, theinternet or the like). Some or all components of the image controller111 may be implemented by hardware. In addition, the image controller111 may be physically formed from a plurality of circuits.

Procedure of Processing by Image Controller 111

FIG. 3 is a flowchart of a procedure of processing by the imagecontroller 111 according to the first embodiment of the presentdisclosure.

First, the image obtainer 201 obtains an input image (step S301: imageobtaining step). Next, the resolution reducer 202 generates lowresolution images from the input image obtained in step S301 (step S302:resolution reduction step). The first detector 211A detects candidatepixels for the correction processing in the low resolution imagesgenerated in step S302, based on the input image obtained in step S301(step S303: first detection step).

Subsequently, the second detector 211B detects pixels other than targetpixels of the correction processing, out of the candidate pixels for thecorrection processing detected in step S303 (step S304: second detectionstep). The corrector 212 performs the specific correction processing forreducing image blurring on the candidate pixels for the correctionprocessing detected in step S303 (excluding the pixels other than targetpixels of the correction processing), in the low resolution imagesgenerated in step S302 (step S305: correction step).

After that, the image output unit 203 outputs the low resolution imagesgenerated in step S302 (the low resolution images having undergone thecorrection processing) to the image generation unit 123 (step S306:output step). The image output unit 203 causes the optical engine 120 toperform the pixel shift display of the low resolution images generatedin step S302 onto the screen 150. Then, the image controller 111terminates the series of steps described in FIG. 3.

Examples of Resolution Reduction Processing

FIGS. 4A and 4B are diagrams illustrating examples of the resolutionreduction processing by the resolution reducer 202 according to thefirst embodiment of the present disclosure. The resolution reducer 202sets the average pixel value of 2×2 pixels in an input image as pixelvalue of one pixel in low resolution images.

For example, the resolution reducer 202 first defines a reference frame410 in which one each box is equivalent to 2×2 pixels in an input image400 (one pixel in low resolution images). To generates a first lowresolution image, the resolution reducer 202 shifts the reference frame410 upward by one pixel from the input image 400 as illustrated in FIG.4A, and sets the average pixel value of the 2×2 pixels in each box aspixel value of one pixel in the low resolution image.

To generate a second low resolution image, the resolution reducer 202shifts the reference frame 410 leftward by one pixel from the inputimage 400 as illustrated in FIG. 4B, and sets the average pixel value of2×2 pixels in each box as pixel value of one pixel in the low resolutionimage.

In the embodiment, the second low resolution image is displayed with aleftward shift from the first low resolution image. Accordingly, theresolution reducer 202 shifts the reference frame 410 leftward asillustrated in FIG. 4B and refers to the pixel values of the 2×2 pixelsin the reference frame 410. To display the second low resolution imagewith a rightward shift from the first low resolution image, theresolution reducer 202 shifts the reference frame 410 rightward andrefers to the pixel values of the 2×2 pixels in the reference frame 410.

In the example of FIG. 4A, for the top line of the reference frame 410,the resolution reducer 202 refers to the blank portions above the inputimage 400. The resolution reducer 202 performs the calculationprocessing of pixel values of the low resolution image, based on theassumption that the blank portions have the same pixel values as thevalues of the pixels on the top line of the input image 400.

In the example of FIG. 4B, for the leftmost line of the reference frame410, the resolution reducer 202 refers to the blank portions on the leftside of the input image 400. The resolution reducer 202 performs thecalculation processing of pixel values of the low resolution image,based on the assumption that the blank portions have the same pixelvalues as the values of the pixels on the leftmost line of the inputimage 400.

Examples of Specific Pattern Detection Processing

FIGS. 5A to 5C are diagrams illustrating examples of the specificpattern detection processing by the detector 211 according to the firstembodiment of the present disclosure. The detector 211 detects theportions of the input image where relatively strong image blurring mayoccur at the time of resolution reduction, as specific patterns. Inparticular, in the embodiment, the detector 211 detects an oblique lineand an isolated point “as specific patterns”. FIGS. 5(a) to 5(c)illustrate the state in which two low resolution images are generatedfrom an input image and are displayed with a pixel shift. In the pixelshift display, the display time of each of the two low resolution imagesis half of the normal time. Therefore, the density of each pixelvisually recognized by the user is half of the normal density.

For example, FIG. 5A (first stage) illustrates an input image 500including a vertical line (100% black and one-dot width). From the inputimage 500, the resolution reducer 202 generates a first low resolutionimage 501 and a second low resolution image 502 illustrated in FIG. 5A(second stage). Then, the low resolution image 502 is displayed with adownward and leftward pixel shift from the low resolution image 501 asillustrated in FIG. 5A (third stage). In the pixel shift display, thedensity of the densest portion (the vertical line in the center) is 50%.That is, in the pixel shift display, the central portion of the verticalline is emphasized relative to the surrounding portions, and thus thereoccurs no relatively strong image blurring.

FIG. 5B (first stage) illustrates an input image 510 including anoblique line (100% black and one-dot width). From the input image 510,the resolution reducer 202 generates a first low resolution image 511and a second low resolution image 512 illustrated in FIG. 5B (secondstage). Then, the low resolution image 512 is displayed with a downwardand leftward pixel shift from the low resolution image 511 asillustrated in FIG. 5B (third stage). In the pixel shift display, thedensity of the densest portion (the central portion of the oblique line)is 25%. That is, in the pixel shift display, the density is low overalland thus there occurs relatively strong image blurring.

FIG. 5C (first stage) illustrates an input image 520 including anisolated point (100% black and one dot). From the input image 520, theresolution reducer 202 generates a first low resolution image 521 and asecond low resolution image 522 illustrated in FIG. 5C (second stage).Then, the low resolution image 522 is displayed with a downward andleftward pixel shift from the low resolution image 521 as illustrated inFIG. 5C (third stage). In the pixel shift display, the density of thedensest portion (the central portion of the isolated point) is 25%. Thatis, in the pixel shift display, the density is low overall and thusthere occurs relatively strong image blurring.

From the foregoing matter, it can be said that an oblique line and anisolated point in the input image are portions where relatively strongimage blurring may occur when the low resolution images are displayedwith a pixel shift. Accordingly, in the embodiment, the detector 211detects an oblique line and an isolated point as specific patterns. Thecorrector 212 performs the correction processing for reducing imageblurring on the portions corresponding to the specific patterns in thelow resolution images.

Examples of Detection Processing of Candidate Pixels for CorrectionProcessing (First Examples)

FIGS. 6A and 6D are diagrams illustrating examples (first examples) ofthe detection processing of candidate pixels for correction processingby the first detector 211A according to the first embodiment of thepresent disclosure. FIGS. 6A to 6D illustrate patterns of 2×2 pixels inan input image (2×2 pixels converted into one pixel in the lowresolution images). Each of the patterns illustrated in FIGS. 6A to 6Dincludes one black pixel and three white pixels. That is, in all thepatterns illustrated in FIGS. 6A to 6D, the average density value of the2×2 pixels is 25%. In the embodiment, the first detector 211A detectsthe pixel in the low resolution image generated based on the averagedensity value of the 2×2 pixels including one black pixel and threewhite pixels as described above (that is, the pixel with a density of25%) as candidate pixel for the correction processing.

Examples of Detection Processing of Pixels Other than Target Pixels ofCorrection Processing (First Examples)

FIGS. 7A and 7B are diagrams illustrating examples (first examples) ofthe detection processing of pixels other than target pixels of thecorrection processing by the second detector 211B according to the firstembodiment of the present disclosure. FIGS. 7A and 7B illustrate 5×5pixels in the low resolution image. Referring to FIGS. 7A and 7B, thepixels set to “1” are candidate pixels for the correction processingdetected by the first detector 211A (in the processing illustrated inFIGS. 6A to 6D). The pixel set to “0” is a pixel not detected as acandidate pixel for the correction processing by the first detector 211A(in the processing illustrated in FIGS. 6A to 6D). The blank pixels maybe either pixels set to “1” or pixels set to “0”.

In the example of FIG. 7A, the four pixels regularly aligned in anoblique direction are all set to “1”. In this case, the second detector211B determines the central one of the 5×5 pixels as an edge pixel of anoblique line (that is, the pixel constituting the specific pattern).Therefore, the second detector 211B does not determine the central pixelas a pixel other than target pixels of the correction processing.

Meanwhile, in the example of FIG. 7B, one of the four pixels regularlyaligned in an oblique direction is set to “0”. In this case, the seconddetector 211B determines that the central one of the 5×5 pixels is notedge pixel of an oblique line (that is, the pixel not constituting thespecific pattern). Therefore, the second detector 211B determines thecentral pixel as a pixel other than target pixels of the correctionprocessing.

The second detector 211B may determine target pixels of the correctionprocessing, instead of determining pixels other than target pixels ofthe correction processing. That is, the second detector 211B maydetermine the pixels to be targeted in the correction processing as“target pixels of the correction processing”, instead of not determiningthe pixels to be targeted in the correction processing as “the pixelsother than target pixels of the correction processing”. In contrast, thesecond detector 211B may determine the pixels not to be targeted in thecorrection processing as “not target pixels of the correctionprocessing”, instead of determining the pixels not to be targeted in thecorrection processing as “pixels other than target pixels of thecorrection processing”. In addition, for the determination on the pixelto be targeted in the correction processing, the second detector 211Bmay determine the pixels other than target pixels of the correctionprocessing to find the target pixels of the correction processing by wayof contradiction.

Examples of Correction Processing (First Examples)

FIG. 8 is a diagram illustrating an example (first example) of thecorrection processing by the corrector 212 according to the firstembodiment of the present disclosure. FIG. 8 (first stage) illustratesan input image 800 including a first oblique line 800A and a secondoblique line 800B. From the input image 800, the resolution reducer 202generates a first low resolution image 801 and a second low resolutionimage 802 illustrated in FIG. 8 (second stage). Then, the low resolutionimage 802 is displayed with a downward and leftward pixel shift from thelow resolution image 801 as illustrated in FIG. 8 (third stage).

The corrector 212 performs emphasis processing on the candidate pixelsfor the correction processing (excluding the pixels other than targetpixels of the correction processing) corresponding to the specificpattern (oblique line) in the low resolution images 801 and 802.

For example, the first oblique line 800A (the downward oblique line inthe input image 800) is equivalent to the pattern illustrated in FIG.7A. Accordingly, the second detector 211B determines the first obliqueline 800A as specific pattern (oblique line). Therefore, in the lowresolution images 801 and 802, the corrector 212 performs emphasisprocessing on the pixels corresponding to the first oblique line 800A.Thus, in the low resolution images 801 and 802, the portion equivalentto the first oblique line 800A, which is originally low in densityoverall, is emphasized. This reduces a difference in density between theportions equivalent to the first oblique line 800A and the secondoblique line 800B in the low resolution images 801 and 802. Therefore,image blurring in the portions equivalent to the first oblique line 800Acan be reduced.

Meanwhile, the second oblique line 800B (the upward oblique line in theinput image 800) is equivalent to the pattern illustrated in FIG. 7B.Accordingly, the second detector 211B does not determine the secondoblique line 800B as specific pattern (oblique line). Therefore, in thelow resolution images 801 and 802, the corrector 212 does not performemphasis processing on the pixels corresponding to the second obliqueline 800B. Accordingly, in the low resolution images 801 and 802, theportion equivalent to the second oblique line 800B, which is originallyhigh in density overall, is not emphasized. This makes it possible to,when the low resolution images 801 and 802 are displayed with a pixelshift, prevent the portion equivalent to the edge of the second obliqueline 800B (for example, a portion P1 illustrated in FIG. 8 (thirdstage)) from being emphasized like jaggy. Therefore, the portionequivalent to the second oblique line 800B can be visually recognized asa smooth straight line.

The specific correction processing by the corrector 212 is not limitedto simple emphasis processing. That is, the specific correctionprocessing by the corrector 212 may be any other processing that allowsreduction of image blurring. For example, the specific correctionprocessing by the corrector 212 may be emphasis processing stronger thanthe general emphasis processing, smoothing processing, or the like.

Examples of Detection Processing of Candidate Pixels for CorrectionProcessing (Second Examples)

FIGS. 9A to 9D are diagrams illustrating examples (second examples) ofdetection processing of candidate pixels for the correction processingby the first detector 211A according to the first embodiment of thepresent disclosure. FIGS. 9A to 9D illustrate patterns of 4×4 pixels inan input image. Each of the patterns illustrated in FIGS. 9A to 9Dincludes 3×3 pixels having a black pixel in the center. The black pixelcan be said to be an isolated point. In the 3×3 pixels, the firstdetector 211A refers to the portion of 2×2 pixels further including oneblack pixel and three white pixels (surrounded with a thick frame in thedrawing). Then, the first detector 211A detects the pixel in the lowresolution image corresponding to the 2×2 pixels (that is, the pixelwith a density of 25%) as candidate pixel for the correction processing.

Examples of Detection Processing of Pixels Other than Target Pixels ofCorrection Processing (Second Examples)

FIG. 10 is a diagram illustrating an example (second example) of thedetection processing of pixels other than target pixels of thecorrection processing by the second detector 211B according to the firstembodiment of the present disclosure. FIG. 10 illustrates 5×5 pixels inthe low resolution image. Referring to FIG. 10, the pixel set to “1” isa candidate pixel for the correction processing detected by the firstdetector 211A (in the processing illustrated in FIGS. 9A to 9D). Thepixels set to “0” are pixels not detected as candidate pixels for thecorrection processing by the first detector 211A (in the processingillustrated in FIGS. 9A to 9D). The shaded pixels may be either pixelsset to “1” or pixels set to “0”.

In the example of FIG. 10, only the central one of the 5×5 pixels is setto “1” and the other pixels are all set to “0”. In this case, the seconddetector 211B determines the central one of the 5×5 pixels as isolatedpoint (that is, the pixel constituting the specific pattern). Therefore,the second detector 211B does not determine that the central pixel is apixel other than target pixels of the correction processing.

In the example of FIG. 10, it is assumed that at least one of the 5×5pixels except for the central pixel is set to “1”, for example. In thiscase, the second detector 211B determines the central one of the 5×5pixels as not isolated point (that is, the pixel not constituting thespecific pattern). Therefore, the second detector 211B determines thatthe central pixel is a pixel other than target pixels of the correctionprocessing.

Examples of Correction Processing (Second Examples)

FIG. 11 is a diagram illustrating an example (second example) of thecorrection processing by the corrector 212 according to the firstembodiment of the present disclosure. FIG. 11 (first stage) illustratesan input image 1100 including a dotted line 1100A. From the input image1100, the resolution reducer 202 generates a first low resolution image1101 and a second low resolution image 1102 illustrated in FIG. 11(second stage). Then, the low resolution image 1102 is displayed with adownward and leftward pixel shift from the low resolution image 1101 asillustrated in FIG. 11 (third stage).

The corrector 212 performs emphasis processing on the candidate pixelsfor the correction processing (excluding the pixels other than targetpixels of the correction processing) corresponding to the specificpattern (isolated point) in the low resolution images 1101 and 1102.

For example, the dotted line 1100A is not equivalent to the patternillustrated in FIG. 10. Accordingly, the second detector 211B determinesthat the black pixels included in the dotted line 1100A are not specificpattern (isolated point). Therefore, in the low resolution images 1101and 1102, the corrector 212 does not perform the emphasis processing onthe pixels corresponding to the dotted line 1100A. This makes itpossible to prevent emphasis of the portion equivalent to the spacingbetween the dots in the dotted line 1100A in the low resolution images1101 and 1102. Accordingly, when the low resolution images 1101 and 1102are displayed with a pixel shift, for example, it is possible to preventthe portion equivalent to the dotted line 1100A from being visuallyrecognized as solid line.

As described above, the image controller 111 of the embodiment detectsthe pixels other than target pixels of the correction processing by thepattern illustrated in FIG. 10 to determine the black pixels as pixelsother than target pixels of the specific correction processing when thespacing between the black pixels is relatively small. Accordingly, theimage controller 111 of the embodiment can prevent the plurality ofisolated black pixels from being visually recognized as connected ones.This advantageous effect can also be obtained in stripe patterns, gridpatterns, polka-dot patterns, and others as well as dotted lines.

Variation of Correction Processing

FIG. 12 is a diagram illustrating an example of a filter used in avariation of the correction processing by the corrector 212 according tothe first embodiment of the present disclosure.

In the first embodiment, the image controller 111 may further include amode selector that selects the image quality mode for the input imagefrom between “natural image mode” (equivalent to a first mode in thepresent disclosure) and “document image mode” (equivalent to a secondmode in the present disclosure). In this case, the corrector 212 maychange the correction processing depending on the image quality modeselected by the mode selector. For example, when the natural image modeis selected, the corrector 212 may not perform the specific correctionprocessing described above in relation to the embodiment (the emphasisprocessing using the result of the detection by the detector 211) butmay perform other correction processing on the low resolution images.Meanwhile, when the document image mode is selected, the corrector 212may perform the specific correction processing described above inrelation to the embodiment on the low resolution images.

A natural image hardly includes a binary oblique line pattern orisolated point pattern. Accordingly, when the natural image mode isselected, the corrector 212 may not perform the specific correctionprocessing described above in relation to the embodiment. This makes itpossible to prevent the corrector 212 from performing unnecessaryprocessing. In addition, it is possible to prevent the corrector 212from performing unnatural emphasis processing on the natural image. Inaddition, when the natural image mode is selected, the corrector 212 mayperform emphasis processing with an unsharp mask as a general emphasisprocessing method instead. In this case, the corrector 212 can performprocessing equivalent to the equation {the image before the emphasisprocessing+(the image before the emphasis processing−smoothing image)×k}to obtain the image having undergone the emphasis processing with anunsharp mask. In the above-described equation, the smoothing image canbe the result of the arithmetic operation by a filter illustrated inFIG. 12, for example. In the above-described equation, k represents aparameter for adjustment of emphasis amount.

Meanwhile, a document image includes many binary oblique line patternsand isolated point patterns. Accordingly, when the document image modeis selected, the corrector 212 may perform the specific correctionprocessing described above in relation to the embodiment. In this case,the corrector 212 may perform emphasis processing on the portionscorresponding to the specific patterns (oblique lines and isolatedpoints) such that the density of the center is similar to the density ofthe portions corresponding to the other neighboring patterns (forexample, vertical lines, transverse lines, and the like). This makes itpossible to reduce image blurring in the portions corresponding to thespecific patterns to the similar level of the portions corresponding tothe other patterns. In addition, the corrector 212 may perform theemphasis processing with an unsharp mask on the portions correspondingto the other patterns as when the natural image mode is selected.

The user may operate the operation unit 103 to select the image qualitymode. Alternatively, the image controller 111 may select automaticallythe image quality mode. In the latter case, the image controller 111 maydetermine automatically whether the target image is a natural image or adocument image by using, for example, the following method. For example,a density projection histogram is generated based on differential imagedata of an input image to determine whether the input image is adocument image or not depending on the magnitudes of variances in thedensity projection histogram. In general, in the density projectionhistogram of a document image, the lines with characters take on largevalues (peaks) and the portions between the lines take on small values(valleys). Accordingly, when relatively large variances are obtained,the target image can be determined as document image.

In the variation, the corrector 212 can perform appropriate correctionprocessing on the low resolution images depending on the image qualitymode of the input image.

Conclusion

As described above, the image controller 111 of the embodiment detectsthe portions of the low resolution images corresponding to the specificpatterns (oblique lines and isolated points) where relatively strongimage blurring may occur. The image controller 111 then performs thespecific correction processing (emphasis processing) for reducing imageblurring on the portions. According to the image controller 111 of theembodiment, when the low resolution images are displayed with a pixelshift, it is possible to reduce image blurring of the projection imageprojected onto the screen 150. Therefore, according to the imagecontroller 111 of the embodiment, it is possible to enhance the qualityof the images displayed with a pixel shift.

In particular, the image controller 111 of the embodiment first detectsthe candidate pixels for the specific correction processing, and thendetects the pixels not matching the specific patterns, out of thecandidate pixels for the specific correction processing, as pixels otherthan target pixels of the specific correction processing. According tothe image controller 111 of the embodiment, it is possible to preventthe specific correction processing from being performed on the pixelsthat would cause trouble if the pixels undergo the specific correctionprocessing.

Second Embodiment

Functional Configuration of Image Controller 111′

Next, a second embodiment of the present disclosure will be describedwith reference to FIGS. 13 to 15. The differences from the firstembodiment will be described here. FIG. 13 is a block diagramillustrating a functional configuration of the image controller 111′according to the second embodiment of the present disclosure. The imagecontroller 111′ of the second embodiment is different from the imagecontroller 111 of the first embodiment (FIG. 2) in further including amode selector 220, a smoothing processor 221, and a sharpener 222.

The mode selector 220 selects the image quality mode. For example, themode selector 220 selects “office document mode”, “still natural imagemode”, or “movie mode”. For example, the mode selector 220 causes theuser to choose one of the image quality modes, and selects the imagequality mode based on the choice. The smoothing processor 221 performssmoothing processing (smoothing filter processing) on the input imageobtained by the image obtainer 201, using a smoothing filter accordingto the image quality mode selected by the mode selector 220. Thesharpener 222 performs sharpening filter processing on the lowresolution images generated by the resolution reducer 202, using asharpening filter.

Procedure of Processing by Image Controller 111′

FIG. 14 is a flowchart of a procedure of processing by the imagecontroller 111′ according to the second embodiment of the presentdisclosure.

First, the image obtainer 201 obtains an input image (step S1401: imageobtaining step). Next, the mode selector 220 selects the image qualitymode (step S1402: selection step). The smoothing processor 221 performsthe smoothing processing on the input image obtained in step S1401according to the image quality mode selected in step S1402 (step S1403:smoothing step). The resolution reducer 202 generates low resolutionimages from the input image having undergone the smoothing processing instep S1403 (step S1404: resolution reduction step). The first detector211A detects the candidate pixels for the correction processing in thelow resolution images generated in step S1404, based on the input imagehaving undergone the smoothing processing in step S1403 (step S1405:first detection step).

Subsequently, the second detector 211B detects the pixels other thantarget pixels of the correction processing, out of the candidate pixelsfor the correction processing detected in step S1405 (step S1406: seconddetection step). The corrector 212 performs the specific correctionprocessing on the candidate pixels for the correction processing(excluding the pixels other than target pixels of the correctionprocessing) detected in step S1405 in the low resolution imagesgenerated in step S1404 (step S1407: correction step).

The sharpener 222 performs the sharpening processing on the lowresolution images having undergone the specific correction processing instep S1407 (step S1408: sharpening step). After that, the image outputunit 203 outputs the low resolution images having undergone thesharpening processing in step S1408 to the image generation unit 123(step S1409: output step). Accordingly, the image output unit 203 causesthe optical engine 120 to perform pixel shift display of the lowresolution images generated in step S1404 on the screen 150. Then, theimage controller 111′ terminates the series of steps described in FIG.14.

Examples of Smoothing Filter and Sharpening Filter

FIGS. 15A to 15D are diagrams illustrating examples of a smoothingfilter and a sharpening filter used by the image controller 111′according to the second embodiment of the present disclosure.

When the office document mode is selected, for example, the smoothingprocessor 221 uses the smoothing filter illustrated in FIG. 15A. Thisallows the smoothing processor 221 to prevent loss of decimal points andthe like.

When the still natural image mode is selected, the smoothing processor221 also uses the smoothing filter illustrated in FIG. 15A. Accordingly,the smoothing processor 221 allows preferable display of still imagesdesired to be higher in definition. When the still natural image mode isselected, the smoothing processor 221 may use the smoothing filterillustrated in FIG. 15B. Accordingly, the smoothing processor 221 canperform relatively weak smoothing processing to display natural imagesin a favorable manner.

When the movie mode is selected, the smoothing processor 221 uses thesmoothing filter illustrated in FIG. 15C. Accordingly, the smoothingprocessor 221 can perform relatively strong smoothing processing todisplay moving images with animated scenes in a gradation-focused smoothmanner.

FIG. 15D illustrates an example of a sharpening filter used by thesharpener 222 in the sharpening filter processing.

As described above, according to the image controller 111′ of the secondembodiment, it is possible to perform appropriate smoothing processingaccording to the selected image quality mode. Therefore, according tothe image controller 111′ of the second embodiment, it is possible tofurther enhance the display image quality at the time of pixel shiftdisplay.

Variation

In the second embodiment, as illustrated in FIG. 16, a determiner 204may further be provided to determine the magnitude of motion of theimage. In this case, when the movie mode is selected, the smoothingprocessor 221 may decide the smoothing filter for use in the smoothingprocessing, based on the result of the determination by the determiner204.

For example, the determiner 204 stores a previous frame image in the lowresolution image in a storage 205. The determiner 204 then determinesthe image motion level from information about the total sum of absolutevalues of the differences between the current frame image and theprevious frame image. Specifically, focusing on some partial displayarea, the determiner 204 calculates the total sum (x) of absolute valuesof the differences between the pixel values of the current frame imageand the pixel values of the previous frame image in that area. When thetotal sum (x) is equal to or less than a predetermined threshold Th_x,the determiner 204 determines that the motion of the current frame imageis small. In contrast, when the total sum (x) is greater than thepredetermined threshold Th_x, the determiner 204 determines that themotion of the current frame image is large. In this case, the determiner204 makes a determination based on the low resolution image, which canreduce the amount of data for use in the determination to ¼ of the inputimage. Further, the determiner 204 makes a determination focusing onsome partial display area, which can reduce the amount of data for usein the determination.

For example, when the determiner 204 determines that the motion of theimage is small, the smoothing processor 221 may use the smoothing filterillustrated in FIG. 15A. Accordingly, the smoothing processor 221 allowsdisplay of the image desired to be higher in definition in a favorablemanner when the motion of the image is relatively small.

For example, when the determiner 204 determines that the motion of theimage is large, the smoothing processor 221 may use the smoothing filterillustrated in FIG. 15C. Accordingly, the smoothing processor 221 canperform relatively strong smoothing processing on the image inrelatively large motion to display the image in a gradation-focusedsmooth manner.

In the above-described variation, when the determiner 204 changes thedetermination result, the smoothing processor 221 may perform thesmoothing processing using the smoothing filter according to the changeddetermination result. In this case, the smoothing processor 221 maychange the smoothing filters in stages so that the strength of thesmoothing processing can change gradually. Accordingly, the smoothingprocessor 221 can reduce a feeling of strangeness resulting from thechanges in the strength of the smoothing processing. For example, it isassumed that the determiner 204 changes the determination result from“large motion” to “small motion”. In this case, the smoothing processor221 may use the smoothing filter illustrated in FIG. 15B for the imageone frame after, and use the smoothing filter illustrated in FIG. 15Afor the image two frame after.

In the above-described variation, the determiner 204 determines themagnitude of the motion of the image in two stages. However, thedetermination stages are not limited to this, but the determiner 204 maydetermine in three or more stages. The smoothing processor 221 may usethe smoothing filter according to each of the determination results inthe stages. Accordingly, the smoothing processor 221 can reduce afeeling of strangeness resulting from the changes in the strength of thesmoothing processing. For example, when the determiner 204 determinesthat the motion of the image is small, the smoothing processor 221 mayuse the smoothing filter illustrated in FIG. 15A for the image one frameafter. For example, when the determiner 204 determines that the motionof the image is normal, the smoothing processor 221 may use thesmoothing filter illustrated in FIG. 15B for the image one frame after.For example, when the determiner 204 determines that the motion of theimage is large, the smoothing processor 221 may use the smoothing filterillustrated in FIG. 15C for the image one frame after.

The above-described embodiments are illustrative and do not limit thepresent invention. Thus, numerous additional modifications andvariations are possible in light of the above teachings. For example,elements and/or features of different illustrative embodiments may becombined with each other and/or substituted for each other within thescope of the present invention.

Each of the functions of the described embodiments may be implemented byone or more processing circuits or circuitry. Processing circuitryincludes a programmed processor, as a processor includes circuitry. Aprocessing circuit also includes devices such as an application specificintegrated circuit (ASIC), digital signal processor (DSP), fieldprogrammable gate array (FPGA), and conventional circuit componentsarranged to perform the recited functions.

What is claimed is:
 1. An image processing device comprising: aresolution reducer to generate, from an input image, low resolutionimages for pixel shift display being lower in resolution than the inputimage; a detector to detect portions of the low resolution imagescorresponding to a specific pattern in which image quality degradationmay occur; and a corrector to perform specific correction processing toreduce the image quality degradation on the portions of the lowresolution images corresponding to the specific pattern.
 2. The imageprocessing device according to claim 1, wherein the specific patternincludes an oblique line.
 3. The image processing device according toclaim 1, wherein the specific pattern includes an isolated point.
 4. Theimage processing device according to claim 1, wherein the detectorincludes: a first detector to detect pixels with a density equal to orless than a predetermined value in the low resolution images ascandidate pixels for the specific correction processing; and a seconddetector to detect pixels matching the specific pattern, out of thecandidate pixels for the specific correction processing, as targetpixels of the specific correction processing.
 5. The image processingdevice according to claim 1, wherein the specific correction processingincludes emphasis processing on the portions corresponding to thespecific pattern.
 6. The image processing device according to claim 5,wherein, in the specific correction processing, density of the portionscorresponding to the specific pattern is enhanced to a similar degree ofdensity of portions corresponding to other neighboring patterns.
 7. Theimage processing device according to claim 1, further comprising a modeselector to select an image quality mode, wherein, when the modeselector selects a first mode corresponding to natural image display asthe image quality mode, the corrector does not perform the specificcorrection processing on the low resolution images, and wherein, whenthe mode selector selects a second mode corresponding to document imagedisplay as the image quality mode, the corrector performs the specificcorrection processing on the low resolution images.
 8. The imageprocessing device according to claim 1, further comprising: a modeselector to select an image quality mode; and a smoothing processor toperform smoothing processing on the input image using a smoothing filteraccording to the image quality mode selected by the mode selector. 9.The image processing device according to claim 8, further comprising adeterminer to determine magnitude of image motion in the low resolutionimages, wherein the smoothing processor performs the smoothingprocessing using a smoothing filter according to the magnitudedetermined by the determiner and the image quality mode selected by themode selector.
 10. An image projection apparatus comprising: the imageprocessing device according to claim 1; and a projector engine toproject the low resolution images generated by the image processingdevice onto a projection plane to display the low resolution images witha pixel shift on the projection plane.
 11. An image processing methodcomprising: generating, from an input image, low resolution images beinglower in resolution than the input image; detecting portions of the lowresolution images corresponding to a specific pattern; and performingspecific correction processing on the portions of the low resolutionimages corresponding to the specific pattern.
 12. An image processingdevice comprising: a resolution reducer to generate, from an inputimage, low resolution images being lower in resolution than the inputimage; a detector to detect portions of the low resolution imagescorresponding to a specific pattern; and a corrector to perform specificcorrection processing on the portions of the low resolution imagescorresponding to the specific pattern.